Sakari Tuominen, Kalle Eerikäinen, Anett Schibalski, Markus Haakana, Aleksi Lehtonen. (2010). Mapping biomass variables with a multi-source forest inventory technique. Silva Fennica vol. 44 no. 1 article id 458. https://doi.org/10.14214/sf.458

Keywords: National Forest Inventory; remote sensing; biomass models; biomass maps

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Map form information on forest biomass is required for estimating bioenergy potentials and monitoring carbon stocks. In Finland, the growing stock of forests is monitored using multi-source forest inventory, where variables are estimated in the form of thematic maps and area statistics by combining information of field measurements, satellite images and other digital map data. In this study, we used the multi-source forest inventory methodology for estimating forest biomass characteristics. The biomass variables were estimated for national forest inventory field plots on the basis of measured tree variables. The plot-level biomass estimates were used as reference data for satellite image interpretation. The estimates produced by satellite image interpretation were tested by cross-validation. The results indicate that the method for producing biomass maps on the basis of biomass models and satellite image interpretation is operationally feasible. Furthermore, the accuracy of the estimates of biomass variables is similar or even higher than that of traditional growing stock volume estimates. The technique presented here can be applied, for example, in estimating biomass resources or in the inventory of greenhouse gases.

Tuominen, Finnish Forest Research Institute, P.O. Box 18, FI-01301 Vantaa, Finland E-mail: sakari.tuominen@metla.fi
Eerikäinen, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: ke@nn.fi
Schibalski, University of Potsdam, Karl-Liebknecht-Strasse 24–25, 14476 Potsdam, Germany E-mail: as@nn.de
Haakana, Finnish Forest Research Institute, P.O. Box 18, FI-01301 Vantaa, Finland E-mail: mh@nn.fi
Lehtonen, Finnish Forest Research Institute, P.O. Box 18, FI-01301 Vantaa, Finland E-mail: al@nn.fi

article id 579, category Research article

Matti Maltamo, Kalle Eerikäinen. (2001). The Most Similar Neighbour reference in the yield prediction of Pinus kesiya stands in Zambia. Silva Fennica vol. 35 no. 4 article id 579. https://doi.org/10.14214/sf.579

Keywords: stand development; difference equations; non-parametric regression; plantation forests

Abstract | View details | Full text in PDF | Author Info

The aim of the study was to develop a yield prediction model using the non-parametric Most Similar Neighbour (MSN) reference method. The model is constructed on stand level but it contains information also on tree level. A 10-year projection period was used for the analysis of stand growth. First, the canonical correlation matrix was calculated for the whole study material using stand volumes at the beginning and at the end of the growth period as independent variables and stand characteristics as dependent variable. Secondly, similar neighbour estimates were searched from the data categories reclassified according to thinnings. Due to this, it was possible to search for growth and yield series which is as accurate as possible both at the beginning and at the end of the growth period. The reliability of the MSN volume predictions was compared to the volumes predicted with the simultaneous yield model. The MSN approach was observed to be more reliable volume predictor than the traditional stand level yield prediction model both in thinned and unthinned stands.

Maltamo, Faculty of Forestry, University of Joensuu, P.O. Box 111, FIN-80101 Joensuu, Finland E-mail: matti.maltamo@forest.joensuu.fi
Eerikäinen, Faculty of Forestry, University of Joensuu, P.O. Box 111, FIN-80101 Joensuu, Finland E-mail: ke@nn.fi

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